anc.clim {phyloclim}

Estimation of Ancestral Climatic Tolerances

Description

This function implements a nonparametric approach to estimate ancestral climatic tolerances proposed by Evans et al. (2009), using ace from the ape package.

Usage

anc.clim(target, posterior = NULL, pno, n = 100, method = "GLS")

Arguments

target

An object of class "phylo"; a best estimate (e.g., ML estimate) of topology on which to summarize mean estimated climatic tolerances, must be ultrametric.

posterior

An object of class "multiPhylo" containing a sample of ultrametric trees from the posterior distribution of a Bayesian tree search to be used for reconstruction of ancestral climatic tolerances. posterior = NULL (the default) means that reconstruction uses target instead.

pno

A data frame containing predicted niche occupancy (PNO) profiles, produced e.g. with pno.

n

An integer: The PNO profile given by pno argument will be resamples n times.

method

A character string specifying the method used for estimation. Two choices are possible: "ML" or "GLS" (see ace for details).

Value

A list containing three elements:

tree

An object of class "phylo", the target tree used in the estimation.

means

A vector containing the means of estimated ancestral climatic tolerances. The elements of means are in the same order as node numbers in element tree.

central.density

A matrix, which for each of the terminal nodes in tree contains the minimum and the maximum of the 80 percent density interval of climatic tolerances (as sampled from the PNO).

Author(s)

Christoph Heibl

References

Evans, M. E. K., S. A. Smith, R. S. Flynn, and M. J. Donoghue. 2009. Climate, niche evolution, and diversification of the 'bird-cage evening primroses' (Oenothera, sections Anogra and Kleinia). Am. Nat. 173: 225-240.

See Also

pno, plotAncClim

Examples

# load phylogeny and PNOs of Oxalis sect. Palmatifoliae
data(tree)
data(PNO)

# choose summer precipitation for analysis
clim <- PNO$PrecipitationWarmestQuarter

# estimate ancestral tolerances
ac <- anc.clim(target = tree, pno = clim, n = 100)

# visualize results
plotAncClim(ac, ylab = "Precipitation of warmest quarter (mm)")